The present application discloses a
sleep monitoring method,
system and storage medium based on
millimeter wave radar, which relates to the field of
millimeter wave monitoring technology. It uses
artificial intelligence-based
signal processing and analysis technology to extract time-frequency features and semantically combine
millimeter wave detection signals and millimeter
wave detection response signals, so as to automatically determine whether
central sleep apnea occurs based on the fusion representation features of the millimeter
wave detection signal and the millimeter wave detection response
signal in
multimodality. In the present application, the millimeter
wave radar can monitor without contacting the
human body, avoiding the inconvenience and interference of wearing sensors in traditional methods, and improving the user's comfort and compliance. At the same time, the millimeter
wave radar has high temporal and spatial resolution, can accurately detect tiny body movements and
breathing changes, and uses
artificial intelligence technology for comprehensive and detailed analysis, which helps to more accurately identify and analyze
sleep apnea problems.